Rapid Matching of Noisy Spectra or Other Signal Patterns

ABSTRACT

A method for use in an object scanning process includes obtaining a reference spectrum that includes a plurality of reference peaks, and comparing the reference spectrum with an input spectrum that has a plurality of input peaks, wherein a number of the reference peaks is less than eight. A method for use in an object scanning process includes obtaining a reference spectrum that includes a plurality of reference peaks, comparing one of the reference peaks with a plurality of input peaks from an input spectrum, comparing another one of the reference peaks with the plurality of input peaks from the input spectrum, and determining a degree of similarity between the reference spectrum and the input spectrum using a result from the acts of comparing.

FIELD

This application relates generally to object scanning, and morespecifically, to systems and methods for identifying substance from anobject scan.

BACKGROUND

The events of Sep. 11, 2001 forced recognition of an urgent need formore effective and stringent screening of airport baggage. The need forsecurity expanded from the inspection of carry-on bags for knives andguns to the complete inspection of checked bags for a range of hazardswith particular emphasis upon concealed explosives. The demonstratedwillingness of terrorists to die in the pursuit of their aims meant that100% passenger-to-bag matching, which could be put in place rapidly, wasnot sufficient to counter an attempt to conceal explosives in checkedbaggage and bring down an airliner. Successful screening for thepresence of explosives presents numerous technological challenges, manyof which are not met in present systems. For example, existing systemsdo not, and cannot, scan luggage rapidly and accurately for detectingthe presence of explosives and hazardous materials. This is because datafrom a luggage scan may have a low signal-to-noise ratio, making itdifficult to accurately scan the luggage. Also, since a luggage scan mayrequire a comparison of the luggage content against a large number ofreference substances, which require significant time, existing luggagescan may not be able to be performed rapidly.

SUMMARY

In accordance with some embodiments, a method for use in an objectscanning process includes obtaining a reference spectrum that includes aplurality of reference peaks, and comparing the reference spectrum withan input spectrum that has a plurality of input peaks, wherein a numberof the reference peaks is less than eight.

In accordance with other embodiments, a system for use in an objectscanning process includes a processor configured for obtaining areference spectrum that includes a plurality of reference peaks, andcomparing the reference spectrum with an input spectrum that has aplurality of input peaks, wherein a number of the reference peaks isless than eight.

In accordance with other embodiments, a method for use in an objectscanning process includes obtaining a reference spectrum that includes aplurality of reference peaks, comparing one of the reference peaks witha plurality of input peaks from an input spectrum, comparing another oneof the reference peaks with the plurality of input peaks from the inputspectrum, and determining a degree of similarity between the referencespectrum and the input spectrum using a result from the acts ofcomparing.

In accordance with other embodiments, a system for use in an objectscanning process includes a processor configured for obtaining areference spectrum that includes a plurality of reference peaks,comparing one of the reference peaks with a plurality of input peaksfrom an input spectrum, comparing another one of the reference peakswith the plurality of input peaks from the input spectrum, anddetermining a degree of similarity between the reference spectrum andthe input spectrum using a result from the acts of comparing.

In accordance with other embodiments, a method for use in an objectscanning process includes obtaining a reference spectrum that includes areference peak, comparing the reference peak with an input peak from aninput spectrum, wherein the act of comparing comprises determininginformation regarding a positional match between the reference peak andthe input peak, and information regarding a magnitude match between thereference peak and the input peak, and using a result from the act ofcomparing to determine a degree of similarity between the referencespectrum and the input spectrum.

In accordance with other embodiments, a system for use in an objectscanning process includes a processor configured for obtaining areference spectrum that includes a reference peak, and comparing thereference peak with an input peak from an input spectrum, wherein theact of comparing comprises determining information regarding apositional match between the reference peak and the input peak, andinformation regarding a magnitude match between the reference peak andthe input peak, and using a result from the act of comparing todetermine a degree of similarity between the reference spectrum and theinput spectrum.

Other and further aspects and features will be evident from reading thefollowing detailed description of the embodiments, which are intended toillustrate, not limit, the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings illustrate the design and utility of embodiments, in whichsimilar elements are referred to by common reference numerals. Thesedrawings are not necessarily drawn to scale. In order to betterappreciate how the above-recited and other advantages and objects areobtained, a more particular description of the embodiments will berendered, which are illustrated in the accompanying drawings. Thesedrawings depict only typical embodiments and are not therefore to beconsidered limiting of its scope.

FIG. 1 illustrates a method for determining a degree of similaritybetween an input spectrum and a reference spectrum in accordance withsome embodiments;

FIG. 2 illustrates a scanning system with a processor for performingembodiments of the functions described herein.

FIGS. 3A-3C illustrates the concept of the technique used in the methodof FIG. 1;

FIGS. 4A and 4B illustrate a luggage scanning system that incorporatesembodiments described herein;

FIG. 5 illustrates some components of a luggage scanning system; and

FIG. 6 is a block diagram of a computer system architecture, with whichembodiments described herein may be implemented.

DESCRIPTION OF THE EMBODIMENTS

Various embodiments are described hereinafter with reference to thefigures. It should be noted that the figures are not drawn to scale andthat elements of similar structures or functions are represented by likereference numerals throughout the figures. It should also be noted thatthe figures are only intended to facilitate the description of theembodiments. They are not intended as an exhaustive description of theinvention or as a limitation on the scope of the invention. In addition,an illustrated embodiment needs not have all the aspects or advantagesshown. An aspect or an advantage described in conjunction with aparticular embodiment is not necessarily limited to that embodiment andcan be practiced in any other embodiments even if not so illustrated.

The embodiments described herein provide a technique to compute a degreeof similarity between a noisy spectrum and a reference spectrum. Thenoisy spectrum (input spectrum) may be an experimentally determinedspectrum, or a spectrum generated for practical purposes, such as aspectrum from an object scanning, etc. The reference spectrum can bepreviously measured or it can come from a known or published library ofspectra for matching. The computation is such that the measured spectrumcan have extra peaks without influencing the computed degree ofsimilarity. Therefore, it is ideal for cases in which the measuredspectrum is from a mixture of compounds, and one is interested indetermining whether the mixture contains a compound that is associatedwith the reference spectrum (e.g., a compound that is desired to bedetected in the mixture).

FIG. 1 illustrates a method 100 for determining a degree of similaritybetween an input spectrum and a reference spectrum in accordance withsome embodiments. First, the input spectrum is obtained (step 102). Inthe illustrated embodiments, the input spectrum is obtained by aprocessor 204 receiving data regarding the input spectrum. The processor204 may be a part of a scanning system 200, that includes a scanningmachine 202, which generates the input spectrum (FIG. 2). In theillustrated embodiments, the scanning machine 202 is a luggage scanningmachine. However, in other embodiments, the scanning machine 202 may beother types of scanning machine, such as a machine for scanning patientsfor medical purposes. Also, in other embodiments, the processor 204 neednot be a part of the scanning system 200, and instead, it may be a partof a processing system that is separate from the scanning system 200. Insuch cases, the processor 204 is configured to receive information fromthe scanning system 200, e.g., using a cable or a wireless communicationdevice. Further, in other embodiments, the input spectrum may have beenalready previously generated and stored in a medium. In such cases, theact of obtaining the input spectrum in step 102 may be accomplished bythe processor 204 retrieving from the medium data for the inputspectrum. Also, in further embodiments, the processor 204 may beintegrated with the scanning machine 202. Devices for generating inputspectrum are well known, and therefore, will not be described in detail.As shown in FIG. 2, the scanning system 200 may further include a userinterface, which includes a screen 206 for displaying information (e.g.,graphics that represent the input spectrum) to a user, and a keyboard208 for allowing the user to input information (e.g., any of theinformation described herein).

Next, the input spectrum is processed to reduce or convert the inputspectrum into a discrete set of peaks (step 104). In the illustratedembodiments, the processor 204 is configured (e.g., programmed and/orbuilt) to smooth the original input spectrum using a Savitsky-Golaysmoothing filter, perform a standard background subtraction, and thenuse the second derivative to determine (e.g., identify) peak locations.Each of the peaks are expressed as (x,y) pairs in which x represents thepeak position and y represents the peak amplitude. In the case of X-raydiffractometry, the peak position may be measured in d-spacing units(Angstroms) for easy comparison with reference spectra, such as thoseavailable in literatures or computer databases.

In any embodiments described herein, the discrete set of peaks (inputpeaks) may themselves be considered as the input spectrum. Thus, as usedin this specification, the term “input spectrum” may refer to theoriginal measured spectrum, or a set of peaks that are obtained fromprocessing of the original measured spectrum. In some embodiments, theinput spectrum is obtained by scanning an object (which may be a solid,a liquid, a gel, or any other materials) that has a mixture ofsubstances, and the input spectrum may have a plurality of sets ofpeaks, with each of the sets representing a substance in the mixture.

Next, the processor 204 determines a degree of similarity between peaksfrom the input spectrum and peaks from a reference spectrum (step 106).The reference spectrum represents a substance, such as an explosive, ora hazardous chemical, that is desired to be detected in the materialbeing tested. The reference spectrum could be determined using the sameor similar technique described above. For example, in some embodiments,a known compound sample may be scanned to generate a reference spectrum,and the reference spectrum may be processed to reduce it to a discreteset of reference peaks as described above. In any embodiments describedherein, the discrete set of reference peaks may themselves be consideredas the reference spectrum. Thus, as used in this specification, the term“reference spectrum” may refer to the original reference spectrum, or aset of reference peaks that are obtained from processing of the originalreference spectrum. In other embodiments, a library, such as a database,of reduced spectra for known compounds that are desired to be matchedmay be used to provide the reference spectrum. In the case of X-raydiffractometry, libraries such as the Powder Diffraction File (PDF) fromthe International Center for Diffraction Data (ICDD) are readilyavailable for use.

In the illustrated embodiments, the processor 204 is configured (e.g.,programmed and/or built) to compute a pre-normalized match score usingthe equation:

${score} = {\sum\limits_{i}\left\lbrack {y_{r,i} \cdot {\sum\limits_{j}\left( {^{- {(\frac{x_{r,i} - x_{m,j}}{a})}^{2}}^{- {(\frac{\ln {({y_{r,i}/y_{m,j}})}}{b})}^{2}}} \right)}} \right\rbrack}$

where (x_(r,i), y_(r,i)) is the position and magnitude of the i'th peakin the reference spectrum and (x_(m,j), y_(m,j)) is the position andmagnitude of the j'th peak in the input spectrum. The values of a and bmay be any constants set to suit a particular application. In someembodiments in which X-ray diffractometry is used, the value 0.005 Å isused for the variable a, and 1.5 is used for the variable b. In someembodiments, the processor 204 may provide a user interface (e.g.,graphics in screen 206) that allows the user to input information foruse in the equation, or to adjust the equation.

The above scoring technique provides several advantageous features. Thefirst exponential term is for measuring a degree of match of thepositional values between peaks from the reference spectrum and peaksfrom the input spectrum. The second exponential term is for measuring adegree of match of the intensity/magnitude between peaks from thereference spectrum and peaks from the input spectrum. Thus, both thepositional values and the intensity values of the peaks are considered.Based on the above scoring algorithm, the score drops exponentially as apeak (input peak) from the input spectrum is more distant from a peak(reference peak) from the reference spectrum. Also, the match scoredrops exponentially with the ratio of the peak heights. Thus, the peaksfrom the input spectrum and the reference spectrum will have a smallmatch score if they are either far away from each other in position(meaning that their energy or d-spacing is very different) or far awayfrom each other in intensity (meaning they are not the same height).

FIGS. 3A-3C illustrate the above concept. FIG. 3A illustrates an inputspectrum 300 that is superimposed with a first reference spectrum 302and a second reference spectrum 304 for comparison. In some embodiments,the screen 206 may display such graphics to a user for allowingvisualization of the comparison between the input spectrum and variousreference spectra. The input spectrum 300 includes five input peaks 300a-300 d. In the illustrated example, each peak 300 is illustrated as aline. However, it should be noted that in other examples, each peak mayhave other configurations, such as a curve with a crest. Also, in otherembodiments, the peak needs not have any configuration, and may berepresented by a value or a point. Thus, as used in this specification,the term “peak” may refer to a line, a curve, a point, a value, anythingthat has a crest characteristic, anything that can be used to representa crest characteristic, or anything that may be reduced to a point (suchas a point with a position and a value) or a line (such as a line with aposition and a height). The first reference spectrum 302 represents afirst substance that is desired to be detected, and includes fivereference peaks 302 a-302 d. The second reference spectrum 304represents a second substance that is desired to be detected, andincludes five reference peaks 304 a-304 d.

FIG. 3B illustrates a comparison between the input spectrum 300 and thefirst reference spectrum 302. A comparison field 306 is created at theend of each reference peak 302 to illustrate the spectrum comparisongraphically. The width of the comparison field 306 represents apositional match threshold, wherein if an input peak is within the widthof the comparison field, then the positional match may be consideredgood, and if an input peak is outside the width, then the positionalmatch may be considered poor. The length of the comparison field 306correlates with a length (or magnitude/intensity) of the reference peak302, in which the higher the reference peak 302, the longer thecomparison field 306 is provided. This places more emphasis on matchesfor higher reference peaks. This is because matches for the lowerreference peaks may not be a strong indication that the material beingtested includes the reference substance. As illustrated in the example,the tips of the input peaks 300 a-300 d are within the respectivecomparison fields 306 of the reference peaks 302 a-302 d. This indicatesthat there is a good match between the input spectrum 300 and the firstreference spectrum 302. If the above described scoring technique isused, the resulting score would provide a relatively high value,indicating a high degree of match between the input spectrum 300 and thereference spectrum 302.

FIG. 3C illustrates a comparison between the input spectrum 300 and thesecond reference spectrum 304. Comparison field 306 is created at theend of each reference peak 304 to illustrate the spectrum comparisongraphically. As illustrated in the example, the tips of the input peaks300 a-300 d are outside the respective comparison fields 306 of thereference peaks 304 a-304 d. This indicates that there is a poor matchbetween the input spectrum 300 and the second reference spectrum 304. Ifthe above described scoring technique is used, the resulting score wouldprovide a relatively low value, indicating a low degree of match betweenthe input spectrum 300 and the reference spectrum 304. Thus, in theabove examples, it may be concluded that the material for the inputspectrum 300 contains the first substance desired to be detected(represented by the first spectrum 302), and does not contain the secondsubstance desired to be detected (represented by the second spectrum304).

Returning to the above equation, the factor of y_(r) in the beginning ofthe above equation is a weighting factor. It is used to make thematching of a relatively intense (higher) peak in the reference spectrumcount more than a matching of a relatively shorter peak. This isadvantageous because matching of higher peaks correlates with a higherprobability that the unknown object being scanned contains a substance(which is represented by the input spectrum) matches with a knownsubstance desired to be detected (which is represented by the referencespectrum).

In the above scoring technique, each of the peaks from the referencespectrum is compared with a plurality of the peaks from the inputspectrum. Such technique for measuring a degree of similarity is basedon a “reverse” matching in which each peak in the reference spectrum iscompared against a plurality of peaks in the input spectrum, not theother way around. Therefore, the overall match score is much lower ifthe input spectrum has missing peaks that are in the reference spectrum,but not necessarily lowered if the input spectrum has extra peaks thatare not in the reference spectrum. This is particularly useful in thesituation in which the input spectrum may represent a mixture ofcompounds, but only one or a subset of which is desired to be detected.For example, a mixture may include 50 input peaks, among which, 5 inputpeaks are from substance S1, 4 input peaks are from substance S2, andthe remaining input peaks may be from other substances or noise. Usingthe reverse matching technique described, a reference spectrum (having 5reference peaks) representing substance S1 is compared against the 50input peaks. If one of the 5 peaks in the reference spectrum is missingin the input spectrum, the overall match score for substance S1 would belower (compared to if all 5 peaks are found in the input spectrum). Onthe other hand, because of the reverse matching technique, the remaining45 peaks from the input spectrum would not affect the match score.Similarly, a reference spectrum (having 4 reference peaks) representingsubstance S2 is compared against the 50 input peaks using the reversematching technique. If one of the 4 peaks in the reference spectrum ismissing in the input spectrum, the overall match score for substance S2would be lower (compared to if all 4 peaks are found in the inputspectrum). On the other hand, because of the reverse matching technique,the remaining 46 peaks from the input spectrum would not affect thematch score.

In some embodiments, when performing step 106, the processor 204 may beconfigured to normalize the score. For example, the match of thereference spectrum to itself may be defined to be unity (or some otherstandard value). In such cases, the processor may be configured todivide the score determined using the above equation by another scorethat is determined by matching the reference spectrum against itself.This normalization makes comparison of match scores across compoundseasier. This is because a match for a certain substance may alwaysproduce a relatively low score, while a match for another substance mayalways produce a relatively high score. As a result, without normalizingthe score, the score itself may not be able to reflect a degree of matchmeaningfully. In some embodiments, the processor 204 may provide a userinterface (e.g., graphics in screen 206) that allows the user to inputinformation for prescribing how the score should be normalized.

In some cases, the reference spectrum is processed to obtain a set ofpeaks that includes only a prescribed number of the largest peaks in thereference spectrum. In such cases, the relatively smaller peaks areexcluded from the reference spectrum. For example, if the prescribednumber is 8, then the processor is configured to determine the eightlargest peaks from the reference spectrum, and use them for comparison,while excluding the remaining smaller peaks from the set. Thus, as usedin this specification, the term “reference spectrum” may refer to areference spectrum in which the number of reference peaks have not beenreduced, or to a processed reference spectrum in which the number ofreference peaks have been reduced. In the illustrated embodiments, thereference spectrum is limited to having less than 8 peaks, and morepreferably, less than 6 peaks, such as 4 or 5 peaks. This isadvantageous in that it makes storage of the reference spectrum easier(because less memory is needed), and requires less resource for storingthe reference spectrum. Also, limiting the number of reference peaks isbeneficial because it allows the reference spectrum to be compared withthe input spectrum quickly, which allows luggage to be scannedefficiently. The inventor has determined that using the above matchingtechnique, the luggage scanning can still be performed accurately basedon a relatively few numbers of peaks. Also, since the relatively smallerpeaks in the reference spectrum may be noise, and they may not bepresent in the input spectrum (i.e., they may not match up with theinput peaks), limiting the number of reference peaks allows matching ofthe input peaks to be performed accurately and efficiently, and reducesthe effect of matching score penalization due to the smaller peaks. Insome embodiments, the input spectrum may also be processed to reduce thenumber of input peaks (e.g., peaks that are relatively smaller inmagnitude/intensity). This may allow noise in the input spectrum to beremoved. Thus, as used in this specification, the term “input spectrum”may refer to an input spectrum in which the number of input peaks havenot been reduced, or to a processed input spectrum in which the numberof input peaks have been reduced. In some embodiments, the processor 204may provide a user interface (e.g., graphics displayed in screen 206)that allows the user to input information for prescribing the number ofreference peaks and/or the number of input peaks.

As illustrated in the above embodiments, the method 100 is simple toexecute, and can be rapidly and accurately applied to unknown compoundsto match them against a library of up to a few hundred, or more,reference compounds. Also, the embodiments of the technique describedherein are more advantageous than spectrum matching algorithms (such asthose in qualitative analysis in spectroscopy) that are for laboratoryapplications. Search methods, such as the Hanawalt search technique andthe Fink search technique, are meant for laboratory applications wherethe quality of spectra is made very high (e.g., the input spectrum hashigh signal-to-noise ratio, and the number of reference peaks forcomparison is high), and ample analysis time is available to compareexperimental spectra to those of any one of thousands of compounds.However, they are not well suited for rapid comparison of materials to alibrary of a few hundred compounds. They are also not well suited forcomparison of materials based on spectra with low signal-to-noise ratio,which may be the case with luggage scanning.

Although the above embodiments have been described with reference todetecting material(s) in luggage, in other embodiments, the techniquedescribed herein may be used to detect material(s) in other situations.For example, in other embodiments, the embodiments of the techniquedescribed herein may be used to detect material(s) in container (e.g.,transport containers at seaport), in food (e.g., in food manufacturingprocess that involves mass production), or in biological subjects (e.g.,humans, farm animals, etc.)

In other embodiments, instead of using the processor 204 for performingthe entire method 100, the processor 204 may perform part(s) of themethod 100. For example, in some embodiments, an additional processor(which may or may not be a part of a scanning machine) may be providedfor performing step 102 of obtaining the input spectrum. In such cases,the additional processor is configured to transmit the input spectrum tothe processor 204 for processing the input spectrum (step 104) andcomparing the input spectrum with reference spectrum(s) (step 106).Also, in other embodiments, the additional processor 204 may performsteps 102, 104. In such cases, the additional processor is configured toprocess the input spectrum, and transmit the processed input spectrum tothe processor 204, which compares the input spectrum with referencespectrum(s) (step 106). As used in this specification, the term“processor” may refer to one or more processing units, any of which maybe implemented using software, hardware, or combination of both. Forexample, in some embodiments, a processing unit may be one or moremicroprocessors, one or more software applications, or any combinationthereof. The processing unit(s) may perform the method 100 or part(s) ofthe method 100.

It should be noted that the method 100 is not limited to the embodimentsdescribed above, and that the method 100 can include other featuresand/or may have other variations. For example, in other embodiments, themethod 100 can include matching of peak width, which could berepresented by another term in the product of exponentials in the aboveequation. Also, in other embodiments, the equation described above mayhave other variations. For example, in other embodiments, the equationmay be expressed in other manners, and/or may have other variables orexpressions for representing any, or a combination, of the featuresdescribed herein. Furthermore, in other embodiments, the processor 204may provide a user interface (e.g., graphics displayed in screen 206)that allows a user to adjust a sensitivity of the comparison test forthe presence a certain reference compound. For example, the sensitivityof the test for a certain compound may be set very high if desired. Insome cases, this may be at the cost of specificity, but for certainapplications in which secondary screening methods are available (such asbaggage scanning for explosive materials or other hazardous materials),this would not be a significant limitation.

As discussed, the method 100 of FIG. 1 may be incorporated as a functionof a scanning system. FIGS. 4A and 4B are a cross-section view and aperspective view, respectively, illustrating one embodiment of an x-raydiffraction system 209 that incorporates embodiments of the method 100described herein. The x-ray diffraction system 209 includes an x-raygenerator 210 having an x-ray source, a pair of collimators 275, and atwo dimensional (2D) flat panel detector (FPD) array 276. The scanningsystem 209 also includes a processor 400 that is configured to performvarious functions described herein. In some embodiments, the processor400 may be the processor 204 described herein. In some embodiments, theprocessor 400 is configured to receive information regarding an inputspectrum from the detector 276, and perform the method 100 describedherein. The x-ray generator 210 is composed of an x-ray tube with alongitudinally extended target and one or more x-ray beams to generatean x-ray sheet beam 220, as further illustrated in FIG. 5. In oneembodiment, the x-ray sheet beam 220 is composed of a continuous highlycollimated x-ray sheet. In an alternative embodiment, the x-ray sheetbeam 220 is composed of multiple close parallel-collimated sub-beamsgenerated by source collimator 215.

As illustrated by FIG. 5, source collimator 215 may include collimatorblocks 217 that operate to limit beam divergence in the x-direction andcollimator foils 218 that operate to limit beam divergence in they-direction. A linear electron gun 213 may be used to generate anelectron beam 219 using cathode 212. The electron beam 219 strikes thesurface 209 of an elongated (e.g., in the range of 1 mm to 2 meters)rotating x-ray target (anode) 211 to generate x-rays that emanatethrough window 216. In one embodiment, target 211 has a width ofapproximately 1 meter. Collimator 215 may be used to collimate thex-rays to produce x-ray sheet beam 220. The shape of the beam may beconfigured by altering the shape of x-ray target 211. In one embodiment,for example, cuts may be made in surface 209 to produce a“picket-fence-like” x-ray sheet beam 220 composed of multiple,individual beams. It should be noted that alternative configurations forthe x-ray generator 210 may be used to produce x-ray sheet beam 220. Inone embodiment, the x-ray generator 210 has a large target 211 surface209 area and can, therefore, operate at high peak and average power. Ifprovided with adequate heat removal capacity, for example liquid coolingof the target 211 via a ferrofluidic seal, it can operate continuouslywith ≧100 KW of input power. The rate at which a diffraction system canacquire data depends upon the detector efficiency. However, once thedetector efficiency has been optimized the data acquisition rate scalesdirectly with the available input x-ray power.

Referring again to FIGS. 4A and 4B, the x-ray sheet beam 220 is directedto a container 240 on a conveyor 250 as the conveyor moves the container240 in direction 243 through the axis of the x-ray sheet beam 220. Thex-ray sheet beam 220 passes vertically through the container 240 to bescanned as it moves along conveyer 250 in direction 243. Alternatively,the container 240 to be scanned need not be on a conveyor 250, but maybe positioned under the x-ray sheet beam 220 through other means. In oneembodiment, the width of the x-ray beam 220 is selected to cover, forexample the whole width of container 240. Alternatively, the x-ray beam220 may have a width greater than the width of conveyor 250. The x-raysheet beam 220 may have widths, for example, in the approximate range of2 mm to 2 meters as determined by the width of the x-ray target 211.

If the x-ray sheet beam 220 intercepts a crystalline material in thecontainer 240 (e.g., a plastic explosive), x-ray photons are diffractedat an angle (θ) 264 to the incident x-ray beam. The angle 264 dependsupon the d-spacing of the atomic planes in the material. Thetrajectories of the diffracted photons lie on cones (e.g., cone 260)with half angle θ centered on the beam axis. The diffracted x-rays 265are detected and their properties measured by a detector assembly 270located below the conveyer 250 and displaced laterally from the path ofthe primary sheet beam so that the detector assembly 270 collects thediffracted x-rays 265. A linear detector 290 may be positionedunderneath the conveyor at the primary axis of the x-ray sheet beam 220to detect undiffracted components of the x-ray sheet beam 220. Thelinear detector (e.g., composed of a line of photoconducting diodes)measures the undiffracted x-ray beam and provides a reference signal andprojection line scan image of container 240.

In one embodiment, the detector assembly 270 may include first andsecond collimators 272 and 274 and a flat panel detector 276. The flatpanel detector 276 may have a conventional TFT structure with ascintillator or photoconductor x-ray direct conversion layer. In oneembodiment, the conversion layer is amorphous and, in particular, mayhave a polycrystalline structure. Alternatively, the conversion layermay have other crystalline structures. The detector assembly 270 may beconfigured to have a narrow acceptance angle of approximately 0.2degrees full width at half maximum (FWHM) by using one or morecollimators placed in front of the flat panel detector 276. Thecollimation planes of the first collimators 272 plates (e.g., plate 283)and the second collimator 274 plates (e.g., plate 293) may besubstantially orthogonal to each other. The collimators ensure that eachpixel 279 of the flat panel detector 276 views a separate area of thebeam, thus dividing the diffracted x-rays 265 into volume elements. Inparticular, first collimator 272 divides the x-ray sheet beam intoindividual vertical (e.g., beam direction 241 mapping to flat paneldetector length 271) segments and second collimator 274 provides theangular resolution for accepting diffracted x-rays of a particularangle. Photons having a particular diffraction angle are selected by theangle of the collimators 275 and flat panel detector 276 with respect tothe primary x-ray sheet beam 220. By tilting the second collimator 274and flat panel detector 276 together, it is possible to scan through thediffraction spectrum in terms of diffraction angle. The first collimator272 need not reside within the detector assembly 270, such that only thesecond collimator 274 and the flat panel detector 276 are movable. In analternative embodiment, the plates of the first and second collimatorsmay be integrated together to form a single collimator having orthogonalplates. Alternatively, other collimator arrangements known in the artmay be used, for examples, hexagonal collimators.

By collecting the diffracted x-rays from each volume element (voxel), itis possible to detect, identify and physically locate substances (e.g.,explosives) within container 240 as it is moved through the x-ray sheetbeam 220. The method is substance-specific and sensitive, with sub-voxeldetection capability because the substance does not need to fill anentire voxel to be identified. The requirement is merely that sufficientmaterial of the substance is intersected by the x-ray sheet beam 220 togive a diffracted photon signal that is above the detector noise level.

The diffracted x-rays may be characterized in different ways, forexamples, by wavelength dispersive (WD) diffraction and energydispersive (ED) diffraction. In wavelength dispersive diffraction, anincident x-ray beam may be composed of monochromatized x-rays containinga narrow range of wavelengths typically 1% or less, centered upon anx-ray emission line characteristic of the x-ray target material, forexample, a K-alpha line, to increase the photon flux in themonochromatized beam. The incident beam may be monochromatized, forexamples, by diffraction off a crystal, by absorption edge filtering,via a graded multilayer mirror, or by other means known in the art. Thelatter has the advantage of improved x-ray collection efficiency.

Components for the above x-ray system 109 have been described in U.S.patent application Ser. No. 11/893,961, filed on Aug. 17, 2007, theentire disclosure of which is expressly incorporated by referenceherein.

The device that can use the method 100 is not limited to the examplesdescribed. In other embodiments, the method 100 may be practiced withother types of testing machine, such as a medical machine for testing apatient, a food scanning machine for testing food, a transport containerscanning system for testing contents in transport containers, etc.

Also, although the embodiments of the method 100 have been describedwith reference to spectrum identification, in other embodiments, themethod 100 may be used for other signal patterns. For example, in otherembodiments, the method 100 can be used to match any signal whichincludes a series of peaks such that peak positions are measured on afixed (not relative) scale. Examples of such signals are spectra (peakspositioned according to a fixed energy scale), spatial patterns of peaksfrom a fixed edge, or time-series patterns of peaks from a standard zerotime reference.

Computer System Architecture

FIG. 6 is a block diagram that illustrates an embodiment of a computersystem 800 upon which an embodiment of the invention may be implemented.Computer system 800 includes a bus 802 or other communication mechanismfor communicating information, and a processor 804 coupled with the bus802 for processing information. The processor 804 may be an example ofthe processor 204 of FIG. 2, or another processor that is used toperform various functions described herein. In some cases, the computersystem 800 may be used to implement the processor 204. The computersystem 800 also includes a main memory 806, such as a random accessmemory (RAM) or other dynamic storage device, coupled to the bus 802 forstoring information and instructions to be executed by the processor804. The main memory 806 also may be used for storing temporaryvariables or other intermediate information during execution ofinstructions to be executed by the processor 804. The computer system800 further includes a read only memory (ROM) 808 or other staticstorage device coupled to the bus 802 for storing static information andinstructions for the processor 804. A data storage device 810, such as amagnetic disk or optical disk, is provided and coupled to the bus 802for storing information and instructions.

The computer system 800 may be coupled via the bus 802 to a display 812,such as a cathode ray tube (CRT) or a flat panel, for displayinginformation to a user. An input device 814, including alphanumeric andother keys, is coupled to the bus 802 for communicating information andcommand selections to processor 804. Another type of user input deviceis cursor control 816, such as a mouse, a trackball, or cursor directionkeys for communicating direction information and command selections toprocessor 804 and for controlling cursor movement on display 812. Thisinput device typically has two degrees of freedom in two axes, a firstaxis (e.g., x) and a second axis (e.g., y), that allows the device tospecify positions in a plane.

The computer system 800 may be used for performing various functions(e.g., calculation) in accordance with the embodiments described herein.According to one embodiment, such use is provided by computer system 800in response to processor 804 executing one or more sequences of one ormore instructions contained in the main memory 806. Such instructionsmay be read into the main memory 806 from another computer-readablemedium, such as storage device 810. Execution of the sequences ofinstructions contained in the main memory 806 causes the processor 804to perform the process steps described herein. One or more processors ina multi-processing arrangement may also be employed to execute thesequences of instructions contained in the main memory 806. Inalternative embodiments, hard-wired circuitry may be used in place of orin combination with software instructions to implement the invention.Thus, embodiments of the invention are not limited to any specificcombination of hardware circuitry and software.

The term “computer-readable medium” as used herein refers to any mediumthat participates in providing instructions to the processor 804 forexecution. Such a medium may take many forms, including but not limitedto, non-volatile media, volatile media, and transmission media.Non-volatile media includes, for example, optical or magnetic disks,such as the storage device 810. Volatile media includes dynamic memory,such as the main memory 806. Transmission media includes coaxial cables,copper wire and fiber optics, including the wires that comprise the bus802. Transmission media can also take the form of acoustic or lightwaves, such as those generated during radio wave and infrared datacommunications.

Common forms of computer-readable media include, for example, a floppydisk, a flexible disk, hard disk, magnetic tape, or any other magneticmedium, a CD-ROM, any other optical medium, punch cards, paper tape, anyother physical medium with patterns of holes, a RAM, a PROM, and EPROM,a FLASH-EPROM, any other memory chip or cartridge, a carrier wave asdescribed hereinafter, or any other medium from which a computer canread.

Various forms of computer-readable media may be involved in carrying oneor more sequences of one or more instructions to the processor 804 forexecution. For example, the instructions may initially be carried on amagnetic disk of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to the computer system 800can receive the data on the telephone line and use an infraredtransmitter to convert the data to an infrared signal. An infrareddetector coupled to the bus 802 can receive the data carried in theinfrared signal and place the data on the bus 802. The bus 802 carriesthe data to the main memory 806, from which the processor 804 retrievesand executes the instructions. The instructions received by the mainmemory 806 may optionally be stored on the storage device 810 eitherbefore or after execution by the processor 804.

The computer system 800 also includes a communication interface 818coupled to the bus 802. The communication interface 818 provides atwo-way data communication coupling to a network link 820 that isconnected to a local network 822. For example, the communicationinterface 818 may be an integrated services digital network (ISDN) cardor a modem to provide a data communication connection to a correspondingtype of telephone line. As another example, the communication interface818 may be a local area network (LAN) card to provide a datacommunication connection to a compatible LAN. Wireless links may also beimplemented. In any such implementation, the communication interface 818sends and receives electrical, electromagnetic or optical signals thatcarry data streams representing various types of information.

The network link 820 typically provides data communication through oneor more networks to other devices. For example, the network link 820 mayprovide a connection through local network 822 to a host computer 824 orto equipment 826 such as a radiation beam source or a switch operativelycoupled to a radiation beam source. The data streams transported overthe network link 820 can comprise electrical, electromagnetic or opticalsignals. The signals through the various networks and the signals on thenetwork link 820 and through the communication interface 818, whichcarry data to and from the computer system 800, are exemplary forms ofcarrier waves transporting the information. The computer system 800 cansend messages and receive data, including program code, through thenetwork(s), the network link 820, and the communication interface 818.

Although particular embodiments have been shown and described, it willbe understood that they are not intended to limit the presentinventions, and it will be obvious to those skilled in the art thatvarious changes and modifications may be made without departing from thespirit and scope of the present inventions. The specification anddrawings are, accordingly, to be regarded in an illustrative rather thanrestrictive sense. The present inventions are intended to coveralternatives, modifications, and equivalents, which may be includedwithin the spirit and scope of the present inventions as defined by theclaims.

1. A method for use in an object scanning process, comprising: obtaininga reference spectrum that includes a plurality of reference peaks; andcomparing the reference spectrum with an input spectrum that has aplurality of input peaks; wherein a number of the reference peaks isless than eight.
 2. The method of claim 1, wherein the act of comparingis performed to determine a degree of similarity between the inputspectrum and the reference spectrum.
 3. The method of claim 1, whereinthe act of comparing is performed using a reverse-matching technique. 4.The method of claim 1, wherein the act of comparing comprisesdetermining a score that represents a degree of similarity between theinput spectrum and the reference spectrum.
 5. The method of claim 4,wherein the score is based at least on a difference between a positionof one of the reference peaks and a position of one of the input peaks,and a ratio calculated using a magnitude of the one of the referencepeaks and a magnitude of the one of the input peaks.
 6. The method ofclaim 4, wherein the score is determined by weighting a matched peakthat has a higher magnitude more than a matched peak that has a lowermagnitude.
 7. The method of claim 4, wherein the act of comparingfurther comprises normalizing the score.
 8. The method of claim 1,wherein the input spectrum is for an object that is being scanned by aluggage scanning machine.
 9. The method of claim 1, wherein the act ofcomparing is performed using a function:${{score} = {\sum\limits_{i}\left\lbrack {y_{r,i} \cdot {\sum\limits_{j}\left( {^{- {(\frac{x_{r,i} - x_{m,j}}{a})}^{2}}^{- {(\frac{\ln {({y_{r,i}/y_{m,j}})}}{b})}^{2}}} \right)}} \right\rbrack}},$or a variation thereof.
 10. A system for use in an object scanningprocess, comprising a processor configured for: obtaining a referencespectrum that includes a plurality of reference peaks; and comparing thereference spectrum with an input spectrum that has a plurality of inputpeaks; wherein a number of the reference peaks is less than eight. 11.The system of claim 10, wherein the processor is configured forperforming the act of comparing to determine a degree of similaritybetween the input spectrum and the reference spectrum.
 12. The system ofclaim 10, wherein the processor is configured for performing the act ofcomparing by using a reverse-matching technique.
 13. The system of claim10, wherein the processor is configured for performing the act ofcomparing by determining a score that represents a degree of similaritybetween the input spectrum and the reference spectrum.
 14. The system ofclaim 13, wherein the score is based at least on a difference between aposition of one of the reference peaks and a position of one of theinput peaks, and a ratio calculated using a magnitude of the one of thereference peaks and a magnitude of the one of the input peaks.
 15. Thesystem of claim 14, wherein the processor is configured to determine thescore by weighting a matched peak that has a higher magnitude more thana matched peak that has a lower magnitude.
 16. The system of claim 13,wherein the processor is further configured for normalizing the score.17. The system of claim 10, wherein the input spectrum is for an objectthat is being scanned by a luggage scanning machine.
 18. The system ofclaim 10, wherein the processor is configured to perform the act ofcomparing by using a function:${{score} = {\sum\limits_{i}\left\lbrack {y_{r,i} \cdot {\sum\limits_{j}\left( {^{- {(\frac{x_{r,i} - x_{m,j}}{a})}^{2}}^{- {(\frac{\ln {({y_{r,i}/y_{m,j}})}}{b})}^{2}}} \right)}} \right\rbrack}},$or a variation thereof.
 19. A method for use in an object scanningprocess, comprising: obtaining a reference spectrum that includes aplurality of reference peaks; comparing one of the reference peaks witha plurality of input peaks from an input spectrum; comparing another oneof the reference peaks with the plurality of input peaks from the inputspectrum; and determining a degree of similarity between the referencespectrum and the input spectrum using a result from the acts ofcomparing.
 20. The method of claim 19, wherein a number of the referencepeaks is less than eight.
 21. The method of claim 19, wherein the actsof comparing are performed using a reverse-matching technique.
 22. Themethod of claim 19, wherein the act of determining the degree ofsimilarity comprises determining a score.
 23. The method of claim 22,wherein the score is determined based at least on a difference between aposition of the one of the reference peaks and a position of one of theinput peaks, and a ratio calculated using a magnitude of the one of thereference peaks and a magnitude of the one of the input peaks.
 24. Themethod of claim 22, wherein the score is determined by weighting amatched peak that has a higher magnitude more than a matched peak thathas a lower magnitude.
 25. The method of claim 22, wherein the act ofdetermining the degree of similarity further comprises normalizing thescore.
 26. The method of claim 19, wherein the input spectrum is for anobject that is being scanned by a luggage scanning machine.
 27. Themethod of claim 19, wherein the acts of comparing and the act ofdetermining the degree of similarity are performed using a function:${{score} = {\sum\limits_{i}\left\lbrack {y_{r,i} \cdot {\sum\limits_{j}\left( {^{- {(\frac{x_{r,i} - x_{m,j}}{a})}^{2}}^{- {(\frac{\ln {({y_{r,i}/y_{m,j}})}}{b})}^{2}}} \right)}} \right\rbrack}},$or a variation thereof.
 28. A system for use in an object scanningprocess, comprising a processor configured for: obtaining a referencespectrum that includes a plurality of reference peaks; comparing one ofthe reference peaks with a plurality of input peaks from an inputspectrum; comparing another one of the reference peaks with theplurality of input peaks from the input spectrum; and determining adegree of similarity between the reference spectrum and the inputspectrum using a result from the acts of comparing.
 29. The system ofclaim 28, wherein a number of the reference peaks is less than eight.30. The system of claim 28, wherein the processor is configured toperform the acts of comparing using a reverse-matching technique. 31.The system of claim 28, wherein the processor is configured to determinea score that represents the degree of similarity.
 32. The system ofclaim 31, wherein the processor is configured to determine the scorebased at least on a difference between a position of the one of thereference peaks and a position of one of the input peaks, and a ratiocalculated using a magnitude of the one of the reference peaks and amagnitude of the one of the input peaks.
 33. The system of claim 31,wherein the processor is configured to determine the score by weightinga matched peak that has a higher magnitude more than a matched peak thathas a lower magnitude.
 34. The system of claim 31, wherein the processoris configured for normalizing the score.
 35. The system of claim 28,wherein the input spectrum is for an object that is being scanned by aluggage scanning machine.
 36. The system of claim 28, wherein theprocessor is configured to perform the acts of comparing and the act ofdetermining the degree of similarity using a function:${{score} = {\sum\limits_{i}\left\lbrack {y_{r,i} \cdot {\sum\limits_{j}\left( {^{- {(\frac{x_{r,i} - x_{m,j}}{a})}^{2}}^{- {(\frac{\ln {({y_{r,i}/y_{m,j}})}}{b})}^{2}}} \right)}} \right\rbrack}},$or a variation thereof.
 37. A method for use in an object scanningprocess, comprising: obtaining a reference spectrum that includes areference peak; comparing the reference peak with an input peak from aninput spectrum, wherein the act of comparing comprises determininginformation regarding a positional match between the reference peak andthe input peak, and information regarding a magnitude match between thereference peak and the input peak; and using a result from the act ofcomparing to determine a degree of similarity between the referencespectrum and the input spectrum.
 38. The method of claim 37, wherein theinformation regarding the positional match comprises a differencebetween a position of the reference peak and a position of the inputpeak.
 39. The method of claim 37, wherein the information regarding themagnitude match comprises a difference between a magnitude of thereference peak and a magnitude of the input peak.
 40. The method ofclaim 37, wherein the act of determining the degree of similaritycomprises determining a score.
 41. The method of claim 40, wherein thescore is determined by weighting a matched peak that has a highermagnitude more than a matched peak that has a lower magnitude.
 42. Themethod of claim 40, wherein the act of determining the degree ofsimilarity further comprises normalizing the score.
 43. A system for usein an object scanning process, comprising a processor configured for:obtaining a reference spectrum that includes a reference peak; comparingthe reference peak with an input peak from an input spectrum, whereinthe act of comparing comprises determining information regarding apositional match between the reference peak and the input peak, andinformation regarding a magnitude match between the reference peak andthe input peak; and using a result from the act of comparing todetermine a degree of similarity between the reference spectrum and theinput spectrum.
 44. The system of claim 43, wherein the informationregarding the positional match comprises a difference between a positionof the reference peak and a position of the input peak.
 45. The systemof claim 43, wherein the information regarding the magnitude matchcomprises a difference between a magnitude of the reference peak and amagnitude of the input peak.
 46. The system of claim 43, wherein theprocessor is configured for determining the degree of similarity bydetermining a score.
 47. The system of claim 46, wherein the processoris configured to determine the score by weighting a matched peak thathas a higher magnitude more than a matched peak that has a lowermagnitude.
 48. The system of claim 46, wherein the processor is furtherconfigured for normalizing the score.